medata here is the Mediterranean dataframe with the following changes:

Some more work needed:

Location and Max Temp

p1 <- ggplot(medata, aes(x = medata$lon, y = medata$lat)) +
  geom_jitter(aes(colour = medata$tmax), show.legend = T) +
  xlab("Longitude") + ylab("Latitude") +
  scale_color_gradient(name = "Max Annual Temp", low = "#3c9ab1", high = "#f22300", na.value = "#899da4")

ggplotly(p1)

1259 rows removed from above plot because they contained NA values.

NA checks

all NAs

medata_na <- subset(medata, is.na(medata))
nrow(medata_na)
## [1] 145042

tmax and tmin

temp_na <- subset(medata, is.na(medata$tmax))
nrow(temp_na)
## [1] 2850

location

loc_na <- subset(medata, is.na(medata$lat))
nrow(loc_na)
## [1] 1259

baktana..

species

spp_na <- subset(medata, is.na(medata$species))
nrow(spp_na)
## [1] 0

good!

species

mpa_na <- subset(medata, is.na(medata$protection))
nrow(mpa_na)
## [1] 637

All of the above can be printed as tables, they’re just extremely long.